The three-week gap between "who's exposed" and "what happens next"
The exposure heatmap is finished. Three departments are flagged amber, one is flagged red, and a short list of roles has landed in the Redeployment Candidate column. That was the hard part, or so it seemed — until the VP of People asks the obvious next question: "So what do we do with these people?"
An exposure score tells you where task-level automation potential is concentrated. It does not tell you what an employee in an exposed role could plausibly move into, how far that move is, or what it would take to get them there. That's a different analysis, run on different data, and it's the one board members and PE owners actually want to see before they'll sign off on a workforce plan.
This article walks through how a skills gap analysis works at the occupation level, how it uses O*NET skill overlap to generate an adjacent-occupation shortlist, and what a defensible reskilling roadmap looks like once you have that shortlist in hand.
What a skills gap analysis actually measures
A skills gap analysis compares the skill, knowledge, and task profile required by a target occupation against the profile of an employee's current occupation, and produces two things: an overlap percentage and a ranked list of the specific descriptors that are missing. It answers "if this person needs to move, where could they move to, and how big is the gap" — a distinct question from exposure, which asks "how much of this role's task mix resembles automatable work."
The two analyses are related but sequential. Exposure scoring identifies which roles belong in the Monitor, Review, or Redeployment Candidate categories. The skills gap analysis takes that Redeployment Candidate list and asks, for each role, which other occupations in the O*NET taxonomy share enough of its underlying skill profile to be a realistic destination. One flags the roles that need attention; the other builds the plan for what happens to the people in them.
Most HR teams don't have a repeatable process for this second step. Gartner's 2024 HR Priorities research found that 86% of HR leaders have not implemented strategic workforce planning, and 66% say the planning they do have is limited to headcount forecasting and struggles to demonstrate ROI. A skills gap analysis is one of the more concrete ways to close that gap — it converts a planning conversation into a ranked, sourced list of destinations and training requirements.
How O*NET turns skill overlap into a reskilling shortlist
The reason occupation-to-occupation comparison is possible at all is that ONET scores every occupation against the same standardized descriptor set. The database covers 1,016 occupational titles (923 at the data level) across roughly 277 descriptors spanning skills, knowledge, abilities, work activities, and tasks, each rated for both importance and level (U.S. DOL, 2025; ONET Resource Center, 2019). Those occupations map onto the 867 detailed occupations defined under the 2018 Standard Occupational Classification (U.S. BLS). The current production release is ONET database v30.3 — confirm the exact version loaded in any tool you evaluate, since ONET updates its descriptors on a regular cycle with a primary annual update in Q3.
Because every occupation is scored on the same scale, two occupations can be compared descriptor by descriptor. For each skill, knowledge area, or ability that both occupations share, the analysis compares the importance and level ratings between the employee's current occupation and a candidate target occupation. Differences are aggregated — typically weighted toward the descriptors that matter most in the current role — into a single overlap percentage. Occupations with high overlap and a short list of missing descriptors are the practical shortlist of "adjacent occupations for reskilling." Occupations with low overlap may still be interesting long-term options, but they represent a much larger training investment.
This article incorporates information from ONET. Used under the CC BY 4.0 license. ONET is a trademark of USDOL/ETA.
A worked example: scoring overlap between two occupations
To make the mechanism concrete, here is a simplified worked example using round, illustrative numbers — not customer data or a real occupation pairing.
Suppose a Customer Service Representative role is flagged as a Redeployment Candidate, and the analysis is testing overlap against a Business Operations Specialist occupation. Three shared descriptors, each scored 0–100 for importance in the current role and level required in the target role:
- Active Listening: 82 in the current role, 70 required in the target role — small gap.
- Critical Thinking: 58 in the current role, 85 required in the target role — moderate gap.
- Data Analysis: 35 in the current role, 80 required in the target role — large gap.
A simple importance-weighted overlap calculation averages how close the current level sits to the required level on each descriptor, weighted by how central that descriptor is to the target role. In this illustration, Active Listening contributes strongly to a high overlap score, Critical Thinking contributes a moderate penalty, and Data Analysis contributes the largest gap — pulling the blended overlap score down and flagging Data Analysis as the priority training need. The output isn't a single verdict; it's a ranked list of which descriptors close the distance fastest, which is exactly the input a training plan needs.
Estimating reskilling effort, not just identifying gaps
An overlap percentage tells you how far apart two occupations are. It doesn't by itself tell you how much time or budget it takes to close that distance — that requires translating each missing descriptor into a training scope, which is a judgment call for the L&D team, not a number the software can manufacture from O*NET data alone.
It's worth grounding that judgment call in independently sourced benchmarks rather than guesswork. The Josh Bersin Company's 2023 research found that external hiring costs roughly 3–5x more than internal placement. SHRM's research separately puts full replacement cost at 50%–200% of an employee's annual salary, with an average cost per hire of $4,129 (SHRM Benchmarking Report, 2016 data). None of these figures tell you what a specific reskilling program will cost — but together they establish that a reskilling investment with real training hours attached is being compared against a real, and often underestimated, external-hire cost baseline, not against zero.
The urgency behind doing this well is also documented at the macro level. The WEF Future of Jobs Report 2025 estimates that 39% of core skills will be transformed or become outdated by 2030, and that of every 100 workers, 59 will need training: 29 are expected to be upskilled in their current role, 19 reskilled or redeployed internally, and 11 are unlikely to receive adequate training. The same report finds 63% of employers cite skill gaps as their biggest barrier to workforce transformation. Lightcast's 2025 research adds a velocity dimension: the skill mix of an average job changed by 32% between 2021 and 2024, and a quarter of jobs saw 75% of their skill requirements turn over in that window. None of this is a claim about your organization specifically — it's the backdrop that explains why a one-time gap analysis goes stale quickly and needs to be re-run on a cycle, not treated as a static document.
Turning overlap scores into an employee reskilling roadmap
Once a Redeployment Candidate role has a ranked list of adjacent occupations and their overlap scores, the roadmap itself has a fairly consistent shape:
- Rank destination occupations by overlap percentage, and shortlist the top two or three realistic options per flagged role rather than every occupation in the database.
- List the specific missing descriptors for each shortlisted destination — these become the actual training curriculum inputs, not a generic "upskilling" line item.
- Sequence by gap size. Small-gap moves are candidates for near-term redeployment; large-gap moves are longer bets that may only make sense for employees with a multi-quarter runway.
- Set a review cadence. Given how quickly skill requirements shift, treat the gap analysis as a living document reviewed on a regular cycle rather than a one-time report.
The roadmap is a planning artifact for a conversation between the employee, their manager, and HR — it is an input to that conversation, not a substitute for it. An overlap score can tell you that a Redeployment Candidate is 78% aligned with a target occupation; it cannot and should not be used to say the move "will" happen, or that the current role "will be" eliminated. That judgment sits with people, not with the software.
What to look for in skills gap analysis software
Because this analysis depends entirely on the quality and transparency of the underlying occupational data, a few criteria matter more than feature count when evaluating a tool:
- O*NET-grounded, not a proprietary black-box taxonomy. You should be able to trace any overlap score back to specific, named O*NET descriptors — importance and level ratings you can independently look up — rather than a scoring method the vendor won't explain.
- Full descriptor coverage. A tool that only compares job titles or a handful of headline skills will miss the knowledge- and ability-level gaps that actually determine training scope.
- Automatic adjacent-occupation shortlists, not just a single gap score for one destination you manually specify.
- A workflow that connects to exposure scoring, so a role identified as a Redeployment Candidate — using a four-dimension rubric scoring cognitive routine, physical routine, social/judgment, and creative task content, each 0–100 — flows directly into the gap analysis without a manual re-entry step.
- Exportable roadmap output your L&D team and finance partners can actually work from.
- Pricing built for a mid-market self-serve budget, so the analysis can be re-run quarterly as skills shift, rather than commissioned as a one-off engagement.
Getting started
If you're building this process for the first time, start with the roles already flagged as Redeployment Candidates from an exposure review, and run the skill overlap comparison against two or three realistic destination occupations per role before trying to scale it organization-wide.
To make the first pass concrete, the Skills-Gap Analysis Worksheet walks through the overlap and effort-estimation steps described above using your own role data. You can browse the rest of the store for related templates, check current pricing for the full platform, or use the ROI calculator to compare a self-serve process against a consulting engagement. For more on how exposure scoring and redeployment planning fit together, see the blog, or join the waitlist if you're not ready to start today.